In recent years, some machine learning methods have been applied to the stroke prediction. In 2010, a combination of Support Vector Machine and Cox Proportional Hazard Model was proposed by Khosla et al. [1]}. Benjamin [2]} implemented an interpretable method using Decision List with Bayesian Analysis to quantify the probability of stroke. Chi-Chun Lee's team [3]}, [4]} compared multiple methods including Deep Neural Network in stroke prediction with Electronic Health Records (EHR). In their research, they focus on the patient's 3 year stroke rate and 8 year stroke rate. However, few of these studies modeled the early screening and prevention of stroke.
